The iron and steel industry, belonging to raw material industry, is a fundamental industry for national economy and plays an important role in the social development. Presently, demands of iron and steel market tend to be complicated, of multi-variety and small-batch, which has an increasing collision with traditional volume production of the iron and steel industry, hence leading to frequent occurrences of production output exceeding order quantity during production process of iron and steel enterprises.
Generally speaking, after the production processes of steel making and continuous casting, surplus slabs exceeding customer's order demand will be stored in the slab yard before hot rolling process as a surplus inventory. Upon investigation, in iron and steel enterprises, surplus inventory accounts for ¼ of total inventory of the slab yard before hot rolling process. The generation of surplus inventory greatly increases production costs, occupies production funds and degrades effective utilization of resources.
Since different kinds of iron and steel products may be obtained by processing the same slab via different technology routing, a solution to the above problem is to match surplus inventory to customer's order before the hot rolling process, namely, assigning surplus slabs to orders with owed quantity in the hot rolling plan.
Presently, surplus slabs assigning in iron and steel enterprises is made manually. Various assigning constraints are involved in the assignment, including steel grades, width, length, weight and due dates specified in orders. Since there are a large number of surplus slabs and orders, manual approach cannot consider various assigning constraints in a comprehensive and accurate manner, which tends to result in unreasonable assignment, leading to high cut-loss of slabs, high inventory costs, low ratio (i.e. hot-charged ratio) of slabs that are loaded into reheating furnace with a higher temperature, assigning the slabs with higher steel grade to orders with low steel grade requirement, hence wasting production resources and energy and increasing comprehensive production costs. Therefore, how to make reasonable utilization of surplus slabs has become a critical technology problem for iron and steel enterprises.
Some domestic and abroad literatures have reported the relevant researches on this kind of problem. Vasko etc. have studied the slab matching problem in which a slab may be divided into two pieces for matching respectively (see, F. J. Vasko, M. L. Cregger, K. L. Stott, L. R. Woodyatt, “Assigning slabs to orders: An example of appropriate model formulation”, Computers & Industrial Engineering, 1994, 26:797-800). An integer planning model is formulated based on discrete feature of the problem. This problem is converted to a transportation problem by adding virtual orders and virtual slabs to be solved with the Bertsekas' network node method.
Dawande etc. also studied the issue of matching slabs and orders with the objectives of minimizing the number of assigned slabs and minimizing cut-loss of slab, in which a slab may be cut into several pieces. (see, M. Sawande, J. Kalagnanam, H. S. Lee, C. Reddy, S. Siegel, M. Trumbo, “The Slab-Design Problem in The Steel Industry”, Interfaces, 2004, 34-215-225). A heuristic algorithm is designed for solving this problem.
In both of the above-mentioned solutions, a surplus slab may be cut into multiple pieces to be assigned to multiple orders. However, a many-to-one optimized matching between surplus slabs and orders is not addressed.